Machine learning techniques for prediction of failure loads and fracture characteristics of high and ultra-high strength concrete beams
The construction sector benefits from the development of artificial intelligence (AI) systems
because they can more accurately forecast the mechanical properties of concrete, which …
because they can more accurately forecast the mechanical properties of concrete, which …
Reliability-based load and resistance factor design of an energy pile with CPT data using machine learning techniques
Energy piles are gaining popularity worldwide as both pile foundations and ground source
heat producers. While considerable research has been conducted on energy pile design …
heat producers. While considerable research has been conducted on energy pile design …
Probabilistic analysis of slope using Bishop method of slices with the help of subset simulation subsequently aided with hybrid machine learning paradigm
The use of probabilistic analysis of slopes as a useful technique for determining the level of
uncertainty in various variables has grown. In this study, a probabilistic analysis of a …
uncertainty in various variables has grown. In this study, a probabilistic analysis of a …
Machine Learning-Aided Monte Carlo Simulation and Subset Simulation
The use of probabilistic analysis (PA) of slopes as an effective method for evaluating the
uncertainty that is so pervasive in variables has become increasingly common in recent …
uncertainty that is so pervasive in variables has become increasingly common in recent …
Reliability‐based state parameter liquefaction probability prediction using soft computing techniques
The state parameter (ѱ) accounts for both relative density and effective stress, which
influence the cyclic stress or liquefaction characteristic of the soil significantly. This study …
influence the cyclic stress or liquefaction characteristic of the soil significantly. This study …
Enhancing deep learning-based slope stability classification using a novel metaheuristic optimization algorithm for feature selection
The evaluation of slope stability is of crucial importance in geotechnical engineering and
has significant implications for infrastructure safety, natural hazard mitigation, and …
has significant implications for infrastructure safety, natural hazard mitigation, and …
Assessment of Stability of Slopes and Remedial Measures in Lesser Himalayan Region: An Overview
Slopes in the lesser Himalayan region are notoriously prone to instability due to complex
geological formations, intense seismic activity, and heavy precipitation patterns. This article …
geological formations, intense seismic activity, and heavy precipitation patterns. This article …
Probabilistic slope stability analysis on a heavy-duty freight corridor using a soft computing technique
This study overviews how to strengthen railway embankments using a geo-grid in the
cohesive soil embankment layer and the Bishop method to determine a safety factor using …
cohesive soil embankment layer and the Bishop method to determine a safety factor using …
The effectiveness of data pre-processing methods on the performance of machine learning techniques using RF, SVR, Cubist and SGB: a study on undrained shear …
In the field of data engineering in machine learning (ML), a crucial component is the process
of scaling, normalization, and standardization. This process involves transforming data to …
of scaling, normalization, and standardization. This process involves transforming data to …
Internal Stability of Mechanically Stabilized Earth Wall Using Machine Learning Techniques
R Mustafa, MT Ahmad - Transportation Infrastructure Geotechnology, 2024 - Springer
This paper proposes an AI-based prediction method for factor of safety (FOS) against rupture
and pull-out failure and examines and compares the applicability and adaptability of k …
and pull-out failure and examines and compares the applicability and adaptability of k …